System and Method For Providing Data Corresponding To Physical Objects

ABSTRACT

There is provided a system and method for providing a visualization of data describing a physical structure. An exemplary method comprises defining an unstructured grid that corresponds to a three-dimensional physical structure, the unstructured grid comprising data representative of a property of interest. The exemplary method also comprises defining a probe as an object that comprises a set of topological elements, at least one of which does not share a common plane. The exemplary method additionally comprises providing a visualization of the unstructured grid data on the geometry defined by the probe.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication 61/373,334, filed Aug. 13, 2010, entitled SYSTEM AND METHODFOR PROVIDING DATA CORRESPONDING TO PHYSICAL OBJECTS, the entirety ofwhich is incorporated by reference herein.

This application also relates to Provisional U.S. Application No.61/311,577, Filed Mar. 8, 2010 and titled “System and Method forProviding Data Corresponding to Physical Objects,” with inventors MarekCzernuszenko et al., and to Provisional U.S. Application No. 61/328,052,filed Apr. 26, 2010 and titled “System and Method for Providing DataCorresponding to Physical Objects,” with inventors Marek Czernuszenko etal., the disclosures of which are incorporated by reference herein intheir entirety for all purposes.

FIELD OF THE INVENTION

The present techniques relate to providing three-dimensional (3D) dataand/or visualizations of data corresponding to physical objects andanalysis thereof. In particular, an exemplary embodiment of the presenttechniques relates to providing visualizations of user-selected portionsof a fully unstructured grid.

BACKGROUND

This section is intended to introduce various aspects of the art, whichmay be associated with embodiments of the disclosed techniques. Thisdiscussion is believed to assist in providing a framework to facilitatea better understanding of particular aspects of the disclosedtechniques. Accordingly, it should be understood that this section is tobe read in this light, and not necessarily as admissions of prior art.

Three-dimensional (3D) model construction and visualization have beenwidely accepted by numerous disciplines as a mechanism for analyzing,communicating, and comprehending complex 3D datasets. Examples ofstructures that can be subjected to 3D analysis include the earth'ssubsurface, facility designs and the human body, to name just threeexamples.

The ability to easily interrogate and explore 3D models is one aspect of3D visualization. Relevant models may contain both 3D volumetric objectsand co-located 3D polygonal objects. Examples of volumetric objects areseismic volumes, MRI scans, reservoir simulation models, and geologicmodels. Interpreted horizons, faults and well trajectories are examplesof polygonal objects. In some cases, there is a need to view thevolumetric and polygonal objects concurrently to understand theirgeometric and property relations. If every cell of the 3D volumetricobject is rendered fully opaque, other objects in the scene will ofnecessity be occluded, and so it becomes advantageous at times to rendersuch volumetric objects with transparency so that other objects may beseen through them. These 3D model interrogation and exploration tasksare important during exploration, development and production phases inthe oil and gas industry. Similar needs exist in other industries.

3D volumetric objects may be divided into two basic categories:structured grids and unstructured grids. Those of ordinary skill in theart will appreciate that other types of grids may be defined on aspectrum between purely structured grids and purely unstructured grids.Both structured and unstructured grids may be rendered for a user toexplore and understand the associated data. There are large numbers ofknown volume rendering techniques for structured grids. Many such knowntechniques render a full 3D volume with some degree of transparency,which enables the user to see through the volume. However, determiningrelations of 3D object properties is difficult, because it is hard todetermine the exact location of semi-transparent data.

A first known way to view and interrogate a 3D volume is to render across-section through the 3D volume. The surface of the intersectionbetween the cross-section and the 3-D volume may be rendered as apolygon with texture-mapped volume cell properties added thereto. In thecase of a structured grid such as seismic or a medical scan, the usercan create cross-sections along one of the primary directions: XY(inline or axial), XZ (cross-line or coronal) and YZ (time slice orsagittal). A traditional cross-section spans the extent of the object.In this case other objects such as horizons, wells or the like arepartially or completely occluded and it is difficult to discern 3Drelationships between objects.

This effect is shown in FIG. 1, which is a 3D graph 100 of a subsurfaceregion. The graph 100, which may provide a visualization of 3D data fora structured grid or an unstructured grid, shows a first cross-section102, a second cross-section 104, a third cross-section 106 and a fourthcross-section 108. Each of the four cross-sections shown in FIG. 1 ischosen to allow a user to see data in a physical property model thatcomprises data representative of a property of interest. However, afirst horizon 110 and a second horizon 112, as well as data displayed oncross-sections 102, 104 and 106 which also may be of interest to a user,are mostly obscured or occluded by the visualizations of the fourcross-sections.

A ribbon section, also called an arbitrary vertical cross-section, isone attempt to make traditional cross-sectional visual representationsmore flexible. To create a ribbon section, the user digitizes a polylineon one face of a volume bounding box. The polyline is extrudedvertically through the volume creating a curtain or ribbon, and thevolumetric data from the intersection of the ribbon with the volume ispainted on the curtain surface.

This concept of arbitrary vertical cross-sections (i.e. ribbon sections)is depicted in FIG. 2, which is a 3D graph 200 of a subsurface regionshowing an arbitrary vertical cross-section defined by a polyline havingtwo segments. The graph 200, which may provide a visualization of 3Ddata for a structured grid or an unstructured grid, shows an arbitraryvertical cross-section defined by a first line segment 202 and a secondline segment 204. Although the arbitrary cross-section shown in FIG. 2is less intrusive than the cross-sections shown in FIG. 1, portions of afirst horizon 206 and a second horizon 208 are still occluded as long asthe arbitrary cross-section is displayed.

U.S. Pat. Nos. 7,098,908 and 7,248,258 disclose a system and method foranalyzing and imaging 3D structured grids using ribbon sections. In onedisclosed system, a ribbon section is produced which may include aplurality of planes projected from a polyline. The polyline includes oneor more line segments preferably formed within a plane. The projectedplanes intersect the 3D volume data set and the data located at theintersection may be selectively viewed. The polyline may be edited orvaried by editing or varying the control points which define thepolyline. Physical phenomena represented within the three-dimensionalvolume data set may be tracked. A plurality of planes may besuccessively displayed in the three-dimensional volume data set fromwhich points are digitized related to the structure of interest tocreate a spline curve on each plane. The area between the spline curvesis interpolated to produce a surface representative of the structure ofinterest, which may for example be a fault plane described by thethree-dimensional volume data set. This may allow a user to visualizeand interpret the features and physical parameters that are inherent inthe three-dimensional volume data set.

Some 3D visualization techniques are suitable for grid structures thatfall between fully structured grids and fully unstructured grids. Onesuch visualization technique relates to the use of reservoir simulationgrids based on geologic models.

As used herein, the term “geologic model” refers to a model that istopologically structured in I,J,K space but geometrically varied. Ageologic model may be defined in terms of nodes and cells. Geologicmodels can also be defined via pillars (columnar cells or 2.5D grid—i.e.a 3D grid extruded from a 2D grid). A geologic model may be visuallyrendered as a shell (i.e. a volume with data displayed only on outersurfaces).

As noted, a geologic model may be thought of as an intermediate stepbetween completely structured and completely unstructured grids. In itssimplest form, a geologic model may comprise a structured grid withdeformed geometry. In a geologic model, cells may be uniquelyaddressable, but their geometries are not entirely implicit. Because ofdeformation, a cell's corner vertices cannot be calculated from just thegrid origin and unit vectors along with the cell's indices. However,each cell is still a polyhedron with six faces. An index may be used tofind its neighbors. Each cell (except the boundary faces) shares sixfaces with other cells, and shares eight corners with other cells.Neighboring cells sharing a vertex may also be addressed. Those ofordinary skill in the art will appreciate that there may be variationson this basic definition of a geologic model. For example, a geologicmodel may comprise keyed out cells, faults and pinch outs. However, thebasic indices still apply and the majority of cells comprise six-facedpolyhedrons. In addition, reservoir simulation grids that are based ongeologic models may retain (i, j, k) cell indices, while explicitlystoring cell geometries.

U.S. Pat. No. 6,106,561 discloses a reservoir simulation grid that isbased on a geologic model. The grid is produced by a simulation griddingprogram that includes a structured gridder. The structured gridderincludes a structured areal gridder and a block gridder. The structuredareal gridder builds an areal grid on an uppermost horizon of an earthformation by performing the following steps: (1) building a boundaryenclosing one or more fault intersection lines on the horizon, andbuilding a triangulation that absorbs the boundary and the faults; (2)building a vector field on the triangulation; (3) building a web ofcontrol lines and additional lines inside the boundary which have adirection that corresponds to the direction of the vector field on thetriangulation, thereby producing an areal grid; and (4) post-processingthe areal grid so that the control lines and additional lines areequi-spaced or smoothly distributed. The block gridder of the structuredgridder will drop coordinate lines down from the nodes of the areal gridto complete the construction of a three dimensional structured grid. Areservoir simulator will receive the structured grid and generate a setof simulation results which are displayed on a 3D viewer for observationby a workstation operator.

U.S. Pat. No. 6,018,497 describes a system having a single grid made upof a mixture of structured and unstructured elements. Unstructured cellsare used around wells because there is higher resolution data in theseareas. Other areas are represented by regular grid cells. The softwaregenerates (i, j, k) indices for the whole grid, so at the end the gridhas the characteristics of a structured grid and it may be classified asa semi-structured grid. In particular, a method and apparatus generatesgrid cell property information that is adapted for use by a computersimulation apparatus which simulates properties of an earth formationlocated near one or more wellbores. An interpretation workstationincludes at least two software programs stored therein: a first programand a second simulation program which is responsive to output dataproduced from the first program for generating a set of simulationresults. The set of simulation results are displayed on a workstationdisplay monitor of the workstation. The first program will: receive welllog and seismic data which indicates the location of each layer of aformation near a wellbore, and then grid each layer of the formation,the grid being comprised of a plurality of cells. The first program willthen generate more accurate data associated with each cell, such as thetransmissibility of well fluid through each cell. The more accurate datafor each cell originating from the first program will be transmitted tothe second simulation program. The second simulation program willrespond to the more accurate data for each cell of the grid from thefirst program by generating a set of more accurate simulation resultsfor each cell of the grid. The second simulation program will overlaythe more accurate simulation result for each cell onto each of thecorresponding cells of the grid which is being generated and displayedon the workstation display by the first program. As a result, theworkstation will display each layer of the earth formation where eachlayer is gridded with a plurality of cells, and each cell has its ownparticular color which corresponds in numerical value to the particularmore accurate simulation result (e.g., pressure or saturation) thatcorresponds to that cell.

Another known attempt to provide a 3D visualization is for a user torender one or more subsets of 3D structured grid data. This technique iscalled volume probing or volume roaming (SGI OpenGL VolumizerProgrammer's Guide) or alternatively just probing, as discussed in U.S.Pat. Nos. 6,765,570 and 6,912,468. The subsets may be created, resized,shaped, and moved interactively by the user within the whole 3D volumedata set. As a subset changes shape, size, or location in response touser input, the image is re-drawn at a rate so as to be perceived asreal-time by the user. In this manner, the user is allegedly able tovisualize and interpret the features and physical parameters that areinherent in the 3D volume data set.

FIG. 3 is a 3D graph 300 of a subsurface region showing an area ofinterest identified by a 3-D data subset. The graph 300, which mayprovide a visualization of 3D data for a structured grid or anunstructured grid, shows a 3D data subset 302. A first horizon 304 and asecond horizon 306 are also shown. In the graph 300, the second horizon306 is partially occluded by the 3D data subset 302. Because of themanner in which the data subset 302 was selected, it cannot easily bemoved to reveal the occluded portion of the second horizon 306.

Another approach to rendering 3D object properties is the use ofisosurfaces, which represent data points having the same or similarproperty values. An isosurface is a 3D analog to a contour line on amap, which connects points of the same elevation. Contour lines on a 2Dmap allow an understanding of the location of mountains and valleys,even though the map is flat. Similarly, isosurfaces can help provide anunderstanding of property distribution in a 3D volume. There are numberof ways to create isosurfaces. One such algorithm is known as a marchingcube algorithm. This technique, however, is not widely used to visualizeseismic data, because seismic property values change by a large amountevery time a sedimentary layer is encountered. If isosurfaces arerendered in seismic data, the result would be a visualization resemblinga large number of pancake-like surfaces stacked on top each other.Accordingly, isosurfaces are not commonly used in the oil and gasindustry.

FIG. 4 is an isosurface rendering 400 of an unstructured grid. Theisosurface rendering 400 comprises a first isosurface 402, a secondisosurface 404, and third isosurfaces 406. Each of the first isosurface402, the second isosurface 404, and the third isosurfaces 406 representsurfaces, each of which represents a common parameter value in a 3Dregion.

Another technique for displaying data corresponding to a 3D region isvolume rendering a space with different attributes corresponding todifferent values of a parameter of interest. For example, differentregions of the 3D region may be shaded in different colors based onvariations in a parameter of interest.

FIG. 5 is a volume rendering 500 of an unstructured grid. The volumerendering 500 comprises a first region 502 and a second region 504. Thefirst region 502 and the second region 504 are shaded differently toindicate that the value of a parameter of interest is in a differentrange in the first region 502 relative to the second region 504.

Another known method of producing visualizations of data represented ina structured grid relates to the use of a probe. A user can quicklyexplore a 3D volume by moving the probe. U.S. Pat. No. 6,765,570discloses a system and method for analyzing and imaging 3D volume datasets using a 3D sampling probe. According to a disclosed system, anumber of sampling probes can be created, shaped, and movedinteractively by the user within the whole 3D volume data set. As thesampling probe changes shape, size, or location in response to userinput, the image is re-drawn at a rate so as to be perceived asreal-time by the user. In this manner, the user is allegedly able tovisualize and interpret the features and physical parameters that areinherent in the 3D volume data set.

U.S. Pat. No. 6,912,468 discloses a method and apparatus forcontemporaneous utilization of a higher order probe in pre-stack andpost-stack seismic domains. The disclosed method includes initiating ahigher order probe at a three-dimensional coordinate in a post-stackseismic volume and instantiating a pre-stack seismic data content forthe higher order probe.

A publication by Speray, D. and Kennon, S., entitled “Volume Probe:Interactive Data Exploration on Arbitrary Grids”, Computer Graphics,November, 1990 describes a technique for probing an unstructured gridusing one or three sheets where a sheet is a planar cutting surface thatmay have limited extents. This functionality is very limiting in thatthe planar sheets can not represent real objects and probing with realobjects is a significant advantage to users.

U.S. Patent Application Publication No. 2009/0303233 describes a systemand method for probing geometrically irregular grids. The disclosurespecifically relates to systems and methods for imaging a 3D volume ofgeometrically irregular grid data. Various types of probes and displaysare used to render the geometrically irregular grid data, in real-time,and analyze the geometrically irregular grid data. The grids describedrequire topologically regular I,J,K indexing. This indexing is arequirement for the described probing technique, which significantlylimits the types of data on which the described method can operate.

Thus, numerous techniques exist for providing visualizations for data inthe context of a structured grid. A system and method of providingvisualizations for data organized in an unstructured grid is desirable.

SUMMARY

An exemplary embodiment of the present techniques comprises a method forproviding a visualization of data describing a physical structure. Theexemplary method comprises defining an unstructured grid thatcorresponds to a three-dimensional physical structure. The unstructuredgrid may comprise data representative of a property of interest. Theexemplary method also comprises defining a probe as an object thatcomprises a set of topological elements, at least one of which does notshare a common plane. The exemplary method additionally comprisesproviding a visualization of the unstructured grid data on the geometrydefined by the probe.

According to an exemplary embodiment of the present techniques, theprobe may comprise a three-dimensional polyhedron, a sphere, or anyclosed three-dimensional surface.

A volume rendering may be produced within a closed space defined by theprobe. A volume rendering may also be produced within a space defined bya distance and/or direction from the probe. Additionally, a structuredgrid may be defined within a space defined by the probe, with a volumerendering being produced therein.

A method according to an exemplary embodiment of the present techniquesmay comprise moving the probe to a different location. In addition, sucha method may comprise providing a visualization of the unstructured gridon the geometry defined by the probe.

According to other aspects, the probe may be defined by a distance, suchas a directionless distance or a vector distance, from a separateobject, which may be a geologic feature of interest. An offset distancemay be defined from a separate object, and the probe may be definedusing a vector distance from the offset. The probe may be defined basedon an intersection of the unstructured grid and a separate object. Asecond probe may be defined as an object that comprises a set oftopological elements, at least one of which does not share a commonplane, and a combined probe may be defined as an object that is theproduct of a Boolean operation on the probes. First and second probesmay be linked such that movement of one of the probes is reflected bymovement of the other of the probes.

According to still other aspects, the definition of the probe may bemodified such that the probe has a changed geometry, and a visualizationof the unstructured grid on the probe may be provided. Modifying thedefinition of the probe may include changing a location of less than allvertices defining the probe, or may include adding or deleting verticesto the probe. Time-based changes to the probe, the probe geometry, thegeometry of the unstructured grid, and/or the data may be accounted for,and a visualization of such time-based changes may be provided.

One exemplary embodiment according to the present techniques relates toa computer system that is adapted to provide a visualization of datadescribing a physical structure. The computer system may comprise aprocessor and a tangible, machine-readable storage medium that storesmachine-readable instructions for execution by the processor. Themachine-readable instructions may comprise code that, when executed bythe processor, is adapted to cause the processor to define anunstructured grid that corresponds to a three-dimensional physicalstructure, the unstructured grid comprising data representative of aproperty of interest. The machine-readable instructions may alsocomprise code that, when executed by the processor, is adapted to causethe processor to define a probe as an object that comprises a set oftopological elements, at least one of which does not share a commonplane. The machine-readable instructions may additionally comprise codethat, when executed by the processor, is adapted to cause the processorto provide a visualization of the unstructured grid data on the geometrydefined by the probe.

In an exemplary computer system, the probe may comprise athree-dimensional polyhedron, a sphere or any closed three-dimensionalsurface.

An exemplary computer system recited may comprise code that, whenexecuted by the processor, is adapted to cause the processor to producea volume rendering within a closed space defined by the probe. Anotherexemplary computer system may comprise code that, when executed by theprocessor, is adapted to cause the processor to produce a volumerendering within a space defined by a distance and/or a direction fromthe probe.

Exemplary computer systems according to the present techniques maycomprise code that, when executed by the processor, is adapted to causethe processor to define a structured grid within a space defined by theprobe. Such exemplary computer systems may also comprise code that, whenexecuted by the processor, is adapted to cause the processor to producea volume rendering within the structured grid.

In addition, exemplary computer systems may comprise code that, whenexecuted by the processor, is adapted to cause the processor to move theprobe to a different location. Such exemplary computer systems may alsocomprise code that, when executed by the processor, is adapted to causethe processor to provide a visualization of the unstructured grid on thegeometry defined by the probe.

An exemplary embodiment of the present techniques relates to a methodfor producing hydrocarbons from an oil and/or gas field using avisualization of data describing a physical structure. Such an exemplarymethod may comprise defining an unstructured grid that corresponds to athree-dimensional physical structure of the oil and/or gas field. Theunstructured grid may comprise data representative of a property ofinterest in the oil and/or gas field. The exemplary method alsocomprises defining a probe as an object that comprises a set oftopological elements, at least one of which does not share a commonplane. A visualization of the unstructured grid data may be produced onthe geometry defined by the probe. The exemplary method additionallycomprises extracting hydrocarbons from the oil and/or gas field based onthe visualization.

DESCRIPTION OF THE DRAWINGS

Advantages of the present techniques may become apparent upon reviewingthe following detailed description and the accompanying drawings inwhich:

FIG. 1 is a 3D graph of a subsurface region showing a combination offour cross-sections with two horizons mostly occluded;

FIG. 2 is a 3D graph of a subsurface region showing an arbitraryvertical cross-section with two horizons partially occluded;

FIG. 3 is a 3D graph of a subsurface region showing a region of interestidentified by a sub-volume probe with one horizon partially occluded;

FIG. 4 is an isosurface rendering of an unstructured grid;

FIG. 5 is a volume rendering of an unstructured grid;

FIG. 6 is a 3D graph showing a probe region in an unstructured gridaccording to an exemplary embodiment of the present techniques;

FIG. 7 is a 3D graph showing the use of cross-sections to describe aprobe region in an unstructured grid according to an exemplaryembodiment of the present techniques;

FIG. 8 is a 3D graph showing a filtered visual representation in anunstructured grid according to an exemplary embodiment of the presenttechniques;

FIG. 9 is a process flow diagram showing a method for providingvisualizations of data that represents a physical object according toexemplary embodiments of the present techniques;

FIG. 10 is a process flow diagram showing a method for producinghydrocarbons from a subsurface region such as an oil and/or gas fieldaccording to exemplary embodiments of the present techniques;

FIG. 11 is a block diagram of a computer network that may be used toperform a method for providing visualizations of data that represents aphysical object according to exemplary embodiments of the presenttechniques;

FIG. 12 is a perspective view of an unstructured grid and a line thatmay be used to define a probe therein;

FIG. 13 is a perspective view of an unstructured grid and a probedefined by an offset from a line;

FIG. 14 is a perspective view of an unstructured grid and a user-definedsurface;

FIG. 15 is a perspective view of an unstructured surface defined by theintersection of the unstructured grid and the user-defined surface ofFIG. 14;

FIG. 16 is a two-dimensional representation of a Boolean operation ontwo probes;

FIG. 17 is a perspective view of an unstructured grid and two probes;

FIG. 18 is a perspective view of the unstructured grid and two probes ofFIG. 17;

FIG. 19 is a perspective view of an unstructured grid and a probe; and

FIG. 20 is a perspective view of the unstructured grid and probe of FIG.19 after some of the vertices defining the probe have been movedrelative to the unstructured grid.

DETAILED DESCRIPTION

In the following detailed description section, specific embodiments aredescribed in connection with preferred embodiments. However, to theextent that the following description is specific to a particularembodiment or a particular use, this is intended to be for exemplarypurposes only and simply provides a description of the exemplaryembodiments. Accordingly, the present techniques are not limited toembodiments described herein, but rather, it includes all alternatives,modifications, and equivalents falling within the spirit and scope ofthe appended claims.

At the outset, and for ease of reference, certain terms used in thisapplication and their meanings as used in this context are set forth. Tothe extent a term used herein is not defined below, it should be giventhe broadest definition persons in the pertinent art have given thatterm as reflected in at least one printed publication or issued patent.

As used herein, the term “3D seismic data volume” refers to a 3D datavolume of discrete x-y-z or x-y-t data points, where x and y are notnecessarily mutually orthogonal horizontal directions, z is the verticaldirection, and t is two-way vertical seismic signal travel time. Insubsurface models, these discrete data points are often represented by aset of contiguous hexahedrons known as cells or voxels. Each data point,cell, or voxel in a 3D seismic data volume typically has an assignedvalue (“data sample”) of a specific seismic data attribute such asseismic amplitude, acoustic impedance, or any other seismic dataattribute that can be defined on a point-by-point basis.

As used herein, the term “cell” refers to a closed volume formed by acollection of faces, or a collection of nodes that implicitly definefaces.

As used herein, the term “computer component” refers to acomputer-related entity, either hardware, firmware, software, acombination thereof, or software in execution. For example, a computercomponent can be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. One or more computer components can residewithin a process and/or thread of execution and a computer component canbe localized on one computer and/or distributed between two or morecomputers.

As used herein, the terms “computer-readable medium” or “tangiblemachine-readable medium” refer to any tangible storage that participatesin providing instructions to a processor for execution. Such a mediummay take many forms, including but not limited to, non-volatile media,and volatile media. Non-volatile media includes, for example, NVRAM, ormagnetic or optical disks. Volatile media includes dynamic memory, suchas main memory. Computer-readable media may include, for example, afloppy disk, a flexible disk, hard disk, magnetic tape, or any othermagnetic medium, magneto-optical medium, a CD-ROM, any other opticalmedium, a RAM, a PROM, and EPROM, a FLASH-EPROM, a solid state mediumlike a holographic memory, a memory card, or any other memory chip orcartridge, or any other physical medium from which a computer can read.When the computer-readable media is configured as a database, it is tobe understood that the database may be any type of database, such asrelational, hierarchical, object-oriented, and/or the like. Accordingly,exemplary embodiments of the present techniques may be considered toinclude a tangible storage medium or tangible distribution medium andprior art-recognized equivalents and successor media, in which thesoftware implementations embodying the present techniques are stored.

As used herein, the term “cross-section” refers to a plane thatintersects a structured grid or an unstructured grid.

As used herein, the term “face” refers to a collection of vertices.

As used herein, the term “filter” refers to the selection of a subset of3D model topological elements (e.g. nodes, faces, cells) based on someselection criteria. Such criteria may be explicit, such as the selectionof elements in a given list, or may be defined procedurally. Suchprocedural criteria may include, but are not limited to, selection ofelements within some particular range or ranges of property values,within some proximity to features of interest, and/or any combination(intersection, union, difference, etc.) of other filters. Filter resultsare often visualized to provide users a better understanding of theirdata. Additional processing might also occur due to filter results.

As used herein, the term “filter object” refers to a 3D construct havinga geometry not defined in terms of a structured or unstructured grid.For example, a filter object for a 3D model may be defined as a wellpath, horizon, polyline, pointset, closed or open surface, or a horizon.

As used herein, the term “horizon” refers to a geologic boundary in thesubsurface structures that are deemed important by an interpreter.Marking these boundaries is done by interpreters when interpretingseismic volumes by drawing lines on a seismic section. Each linerepresents the presence of an interpreted surface at that location. Aninterpretation project typically generates several dozen and sometimeshundreds of horizons. Horizons may be rendered using different colors sothat they stand out in a 3D visualization of data.

As used herein, the term “I,J,K space” refers to an internal coordinatesystem for a geo-cellular model, having specified integer coordinatesfor (i,j,k) for consecutive cells. By convention, K represents avertical coordinate. I,J,K space may be used as a sample space in whicheach coordinate represents a single sample value without reference to aphysical characteristic.

As used herein, the term “node” refers to a point defining a topologicallocation in I,J,K space. If a split or fault condition is associatedwith the node, that node may have more than one point associatedtherewith.

As used herein, the term “plane” refers to a two-dimensional surface. Aplane may be flat or curved.

As used herein, the term “probe” refers to a 3D object that is used todisplay grid data. Probes may be open or closed surfaces, horizons,faults, 3D models, polylines, wells, point sets, ribbon sections (i.e.traverses, vertical arbitrary cross-sections) or any other 3D construct.A probe visualization algorithm displays grid data on the probe orvolume renders the grid data inside a closed area defined by the probe.

As used herein, the term “structured grid” refers to a matrix of volumedata points known as voxels. Structured grids may be used with seismicdata volumes.

As used herein, the term “seismic data” refers to a multi-dimensionalmatrix or grid containing information about points in the subsurfacestructure of a field, where the information was obtained using seismicmethods. Seismic data typically is represented using a structured grid.Seismic attributes or properties are cell- or voxel-based. Seismic datamay be volume rendered with opacity or texture mapped on a surface.

As used herein, the term “simulation model” refers to a structured gridor an unstructured grid with collections of points, faces and cells.

As used herein, the term “stacking” is a process in which traces (i.e.,seismic data recorded from a single channel of a seismic survey) areadded together from different records to reduce noise and improveoverall data quality. Characteristics of seismic data (e.g., time,frequency, depth) derived from stacked data are referred to as“post-stack” but are referred to as “pre-stack” if derived fromunstacked data. More particularly, the seismic data set is referred tobeing in the pre-stack seismic domain if unstacked and in the post-stackseismic domain if stacked. The seismic data set can exist in bothdomains simultaneously in different copies.

As used herein, the term “topological elements” refers to the buildingblocks of an object. Points, faces, or cells are the most commonexamples.

As used herein, the term “unstructured grid” refers to a collection ofcells with arbitrary geometries. Each cell can have the shape of aprism, hexahedron, or other more complex 3D geometries. When compared tostructured grids, unstructured grids can better represent actual datasince unstructured grids can contain finer (i.e. smaller) cells in onearea with sudden changes in value of a property, and coarser (i.e.larger) cells elsewhere where the value of the property changes moreslowly. Finer cells may also be used in areas having more accuratemeasurements or data certainty (for example, in the vicinity of a well).The flexibility to define cell geometry allows the unstructured grid torepresent physical properties better than structured grids. In addition,unstructured grid cells can also better resemble the actual geometriesof subsurface layers because cell shape is not restricted to a cube andmay be given any orientation. However, all cell geometries need to bestored explicitly, thus an unstructured grid may require a substantialamount of memory. Unstructured grids may be employed in connection withreservoir simulation models. Note that the term unstructured gridrelates to how data is defined and does imply that the data itself hasno structure. For example, one could represent a seismic model as anunstructured grid with explicitly defined nodes and cells. The resultwould necessarily be more memory intensive and inefficient to processand visualize than the corresponding structured definition.

As used herein, the terms “visualization engine” or “VE” refer to acomputer component that is adapted to present a model and/orvisualization of data that represents one or more physical objects.

As used herein, the term “voxel” refers to the smallest data point in a3D volumetric object. Each voxel has unique set of coordinates andcontains one or more data values that represent the properties at thatlocation. Each voxel represents a discrete sampling of a 3D space,similar to the manner in which pixels represent sampling of the 2Dspace. The location of a voxel can be calculated by knowing the gridorigin, unit vectors and the i, j, k indices of the voxel. As voxels areassumed to have similar geometries (such as cube-shaped), the details ofthe voxel geometries do not need to be stored, thus structured gridsrequire relatively little memory. However, dense sampling may be neededto capture small features, therefore increasing computer memory usagerequirements.

Some portions of the detailed description which follows are presented interms of procedures, steps, logic blocks, processing and other symbolicrepresentations of operations on data bits within a computer memory.These descriptions and representations are the means used by thoseskilled in the data processing arts to most effectively convey thesubstance of their work to others skilled in the art. In the presentapplication, a procedure, step, logic block, process, or the like, isconceived to be a self-consistent sequence of steps or instructionsleading to a desired result. The steps are those requiring physicalmanipulations of physical quantities. Usually, although not necessarily,these quantities take the form of electrical or magnetic signals capableof being stored, transferred, combined, compared, and otherwisemanipulated in a computer system.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the followingdiscussions, it is appreciated that throughout the present application,discussions using the terms such as “defining”, “selecting”,“displaying”, “limiting”, “processing”, “computing”, “obtaining”,“predicting”, “producing”, “providing”, “updating”, “comparing”,“determining”, “adjusting” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that transforms data represented as physical (electronic) quantitieswithin the computer system's registers and memories into other datasimilarly represented as physical quantities within the computer systemmemories or registers or other such information storage, transmission ordisplay devices. Example methods may be better appreciated withreference to flow diagrams.

While for purposes of simplicity of explanation, the illustratedmethodologies are shown and described as a series of blocks, it is to beappreciated that the methodologies are not limited by the order of theblocks, as some blocks can occur in different orders and/or concurrentlywith other blocks from that shown and described. Moreover, less than allthe illustrated blocks may be required to implement an examplemethodology. Blocks may be combined or separated into multiplecomponents. Furthermore, additional and/or alternative methodologies canemploy additional, not illustrated blocks. While the figures illustratevarious serially occurring actions, it is to be appreciated that variousactions could occur concurrently, substantially in parallel, and/or atsubstantially different points in time.

As set forth below, exemplary embodiments of the present techniquesrelate to the investigation, interrogation and visualization ofunstructured volumetric objects. More specifically, exemplaryembodiments relate to the provision of visualizations of datarepresented in the form of an unstructured grid using techniques ofprobe selection and filtering.

An exemplary embodiment of the present techniques relates to avisualization engine or VE that supports volume rendered unstructuredgrids. Moreover, a VE according to the present techniques supportscreating an unstructured probe type that allows clients to volume renderinside a probe or to render properties on the probe faces.

A probe object according to the present technique may comprise anotherobject describing a physical structure (e.g. a well, horizon, fault, oreven another 3D model) or may be a non-planar synthetic object createdby a user. Further, probe objects according to the present techniquescan be closed and contain volume and allow for volume rendering insidethis closed volume.

According to an exemplary embodiment of the present techniques, a probeprovides a visualization of a model on the probe geometry. Moreover, thepresent techniques relate to identifying model data with a 3D objectthat is not defined by the geometry of the grid associated with themodel data. Examples of probing according to an exemplary embodiment ofthe present techniques include selecting the unstructured grid data thatis intersected by a well, or contained by a closed surface, or withinsome distance to another object and displaying the data on the probe.This is in contrast to a filter, which delineates a subset of thetopological elements belonging to a model and visualizes the subset.

Exemplary embodiments of the present technique may be combined withother techniques to provide new workflows. For example, a model A may befiltered based on a surface B. The result may be used to probe a modelC.

In addition, an exemplary embodiment of the present technique may beused on a completely unstructured data model and does not require anindex domain. Thus, such an exemplary embodiment may operate in asimilar manner on both geologic and simulation models as well as anunstructured grid.

FIG. 6 is a 3D graph showing a probe region in an unstructured gridaccording to an exemplary embodiment of the present techniques. Thegraph is generally referred to by the reference number 600. A legend 602shows a directional reference for an x-axis, a y-axis and a z-axis.

The graph 600 shows an unstructured grid 604, which may correspond to aportion of a 3D space. The unstructured grid 604 represents a pluralityof cells, each of which embodies data about a property of interest forthe 3D space. Moreover, the cells are defined because they represent aregion of the 3D space having a common value (or range of values) forthe property of interest. The cells of the unstructured grid 604 are,therefore, defined by their data content relative to a property ofinterest (for example, porosity). The cells do not have a uniformgeometry.

According to an exemplary embodiment of the present techniques, novisualization of the property of interest is shown for most of theunstructured grid 604. Moreover, the graph 600 shows a visualization ofa probe region 606. The probe region 606, which may be referred to as avolume of interest herein, is located by a user in a portion of theunstructured grid for which the user wishes to observe the property ofinterest. In the exemplary embodiment shown in FIG. 6, the probe region606 is generally spherical. Those of ordinary skill in the art willappreciate that the shape of the probe region may take the form of awide range of geometries depending on specific applications. Accordingto an exemplary embodiment of the present techniques, a probe is anobject that comprises a set of topological elements, at least one ofwhich does not share a common plane with the other topological elementsthat define the probe. This probe configuration allows a user to obtaindata around a wide range of subsurface features including horizons, wellpaths, faults, surfaces, arbitrary vertical sections, arbitrary volumes,or the like.

Probes can be created directly from one of the objects mentioned aboveor by some operation on them. A common example would be the creation ofa probe that is a closed surface that represents some distance from ageologic feature of interest such as a horizon or fault. Thus the probewould render unstructured grid data only within a specified distance ofthe geologic feature of interest. In some cases a vector distance ismore useful. In this case the distance is calculated along a 3D vector.Another probe creation operation would be creating a probe that is aniso-surface of one property or a probe object that represents theoverlapping containment with the unstructured grid and a differentmodel. FIG. 12 depicts an unstructured grid 1200 comprised of aplurality of variously shaped cells 1202. A line 1204 may be arbitrarilydefined by the user. Alternatively, the user may define the line toapproximate the location of a geologic or geometric feature present inthe unstructured grid. Such selection may also be done automaticallyusing a software-based feature recognition process. A probe may bedefined as a closed surface within a specified distance from line 1204or a vector distance from line 1204. Only unstructured grid data withinthe distance would be displayed. A probe defined by a directionlessdistance from line 1204 would resemble a tube or pipe surrounding theline, while a probe defined by a vector distance from the line wouldresemble a series of segmented planes having a height of the desiredvector distance and extending from the line in the vector direction. Thevector-defined probe could be created using a single vector that extendsin one direction, or could also be created using two vectors havingopposing directions. Still another example of a vector-defined probe isshown in FIG. 13, in which line 1204 has added to it an offset 1302 inthe z-direction of the unstructured grid. A probe 1306 is defined by avector distance in the opposite direction of the offset, which willextend back through the unstructured grid. Line 1204 is only one exampleof the many shapes or forms from which a distance may be measured todefine a probe.

Another useful technique is to create a probe that matches the geometryof a user-defined object or a subsurface object such as a horizon orfault, but has the topological intersection of both the unstructuredgrid and the user-defined or subsurface object. For example, FIG. 14depicts an unstructured grid 1400 and a user-defined surface 1402. Theintersection of the unstructured grid and the user-defined surface isshown in FIG. 15 as an unstructured surface 1502, which may then be usedas a probe in the unstructured grid. Unstructured surface 1502 mayinclude the contours or topological features of the unstructured grid1400 and the user-defined surface 1402. Doing so allows for easy mappingof unstructured grid properties to the created probe for display.

Still another useful technique is to combine probes, which can be donein various ways. For example, a Boolean operation such as intersection,union or complement, may be used to combine multiple probes to createone new combined probe. FIG. 16 is a two-dimensional representation of afirst probe 1602 and a second probe 1604 defined according to thetechniques described herein. The Boolean operation of union combines thetwo probes to make a single probe. The Boolean operation intersectiondefines a new, combined probe only where the two probes intersect. Thisis shown in FIG. 16 with combined probe 1606.

Yet another useful technique is to link probes together such thatgeometric changes to one probe, such as translation, rotation orediting, are reflected in the other linked probes. As shown in FIG. 17,a translation of a first probe 1702 in the direction shown by arrow 1704moves second probe 1706 in the same direction, as shown in the newpositions of the first and second probes 1702, 1706 in FIG. 18.

As shown in FIG. 6, a VE according to exemplary embodiments of thepresent techniques provides a visualization of cell data for cells thatinteract with the probe region 606. Moreover, the visualization of theunstructured grid data is displayed on the geometry defined by theprobe. The visualization may include a representation of datacorresponding to the property of interest. For example, datacorresponding to the cells within the probe region 606 may be shown indifferent colors on the geometry defined by the probe to indicatedifferent values of the property of interest.

To create a visualization by selecting a probe region or volume ofinterest, a three-dimensional structure such as a sphere or a polyhedronis created in such a way that it at least partially intersects anunstructured grid. The three-dimensional structure represents a proberegion. The probe region may be chosen based on any criteria that a usermay wish to employ. In particular, the user may select an area for theprobe region for which a visualization of data corresponding to theproperty of interest is desired.

A property of the unstructured grid may then be rendered on the faces ofthe three-dimensional structure of the probe region. For example, avalue or color corresponding to each cell in the probe region may bedisplayed as a portion of the visualization. Alternatively, anunstructured grid property may be volume rendered on the interior of thethree-dimensional structure of the probe region. As yet anotheralternative, a structured grid may be created within thethree-dimensional volume of interest. A property of the unstructuredgrid may be sampled and used to volume render the structured grid. Afterthe application of any of these alternative techniques, thethree-dimensional volume of interest may be moved and the associatedgrid property re-rendered.

In addition, one or more vertices of the probe may be moved, deleted oradded. The corresponding property may then be re-rendered on thegeometry of the probe. As an example, FIG. 19 depicts a probe 1900 in anunstructured grid 1902. Probe 1900 is composed of several verticalsections 1904 a, 1904 b, 1904 c defined by vertices such as vertices1906 a, 1906 b, 1906 c, 1906 d, 1906 e, 1906 f, 1906 g, and 1906 h. FIG.20 shows probe 1900 after vertices 1906 a, 1906 b, 1906 e, and 1906 fhave been moved to different positions relative to the unstructuredgrid, while vertices 1906 c, 1906 d, 1906 g, and 1906 h remainunchanged. Thus, as opposed to moving the entire probe, the shape of theprobe can be modified by adding to, deleting from, or modifying portionsof the existing probe geometry.

Another example of changes to the probe is when the probe and/or thegeometric definition of the probe changes as a function of time.Further, the unstructured grid and/or the unstructured grid data whichis visualized on the probe may also change over time. Any and all ofthese time-based changes may be accounted for and visualized using theaspects and techniques disclosed herein and/or U.S. application Ser. No.12/791,609, filed Jun. 1, 2010, titled “System and Method for Providinga Time-Based Representation of Data” with inventors Timothy A. Chartrandet al., the disclosure of which is incorporated by reference herein inits entirety for all purposes.

A region within a probe may be volume rendered as a structured grid. Forthe case of structured grid volume rendering, a box probe on anunstructured grid may be volume rendered by replacing a six-sided probewith a structured grid and sampling onto that grid for volume renderingof the probe. The user would be able to tune the granularity of thesampling relative to the interactive requirements to achieve a balancebetween interaction and image quality.

FIG. 7 is a 3D graph showing the use of cross-sections to describe aprobe region in an unstructured grid according to an exemplaryembodiment of the present techniques. The graph is generally referred toby the reference number 700. The graph 700 is useful in explaining thedefinition of a 3D probe region using cross-sections.

The graph 700 comprises an unstructured grid 702. For purposes ofsimplicity, no constituent cells of the unstructured grid 702 are shownin FIG. 7. The unstructured grid 702 is intersected by a firstcross-sectional plane 704 and a second cross-sectional plane 706. As setforth above, the first cross-sectional plane 704 and a secondcross-sectional plane 706 may be chosen by the user based on a widerange of considerations. Moreover, the selection of the probe region andsubsequent definition thereof are performed by a user based on one ormore properties of the 3D space represented by the unstructured gridthat may be of interest to the user. An exemplary embodiment of thepresent techniques employs a probe that comprises an object defined by aset of topological elements, at least one of which does not share acommon plane.

The first cross-sectional plane 704 and the second cross-sectional plane706 define a 3D polyhedronal probe region 708. Exemplary embodiments ofthe present techniques may comprise a VE that is adapted to render avisualization of data corresponding to a property of interest on thesurfaces of the 3D polyhedronal probe region 708. In addition, othertechniques may be employed to provide a useful visualization using the3D polyhedronal probe region 708. For example, the interior of the 3Dpolyhedronal probe region 708 may be represented as a structured grid,which may be volume rendered.

FIG. 8 is a 3D graph showing a filtered visual representation in anunstructured grid according to an exemplary embodiment of the presenttechniques. The graph is generally referred to by the reference number800. A legend 802 shows a directional reference for an x-axis, a y-axisand a z-axis.

The graph 800 shows an unstructured grid 804, which may correspond to aportion of a 3D space. The unstructured grid 804 represents a pluralityof cells, each of which embodies data about a property of interest forthe 3D space. Moreover, the cells are defined because they represent aregion of the 3D space having a common value (or range of values) forthe property of interest. As described herein, a filtering techniqueaccording to the present techniques allows a user to define a filterobject corresponding to an item of interest such as a well path. Thedefinition of the filter object is not based on cells in a gridcorresponding to a physical property model. The filter object providesdata from the grid cells for cells that are intersected by the filterobject.

According to an exemplary embodiment of the present techniques, novisualization of the property of interest is shown for most of theunstructured grid 804. However, a visualization of cell data may beprovided based on one or more filter criterion selected by a user. Byway of example, the graph 800 includes a well path 806, which is anexample of a fixed object in the 3D region. A user may be interested inviewing a visualization of data corresponding to the property ofinterest for cells that meet a specific filter criterion. As shown inFIG. 8, the graph 800 includes a filter region 808, which includes cellsthat are within a specific user-selected filter distance of the wellpath 806.

A visualization of the filter region 808 shows the cell values for theproperty of interest for the cells that meet the filter criterion. Forexample, the cells within the filter region 808 may be represented bycorresponding data values or may be shown in different colors toindicate different values of the property of interest.

In general, a visualization may be created using filtering by selectinga range of a cell geometry or one or more cell property values. Cellsthat meet the filtering criteria are selected. This process may berepeated as desired for any number of filters.

If multiple filters are used, the different filters may be combinedusing Boolean operations such as UNION, SUBTRACT, NEGATE, INTERSECTIONor the like. Cells may then be selected based on the result of thechosen Boolean operation(s). A visualization of the selected cells maythen be created.

Examples of filters that may be created by Boolean operations include,without limitation, property thresholds, distances from other objects,surface or line intersections, i,j,k topological identification, userdefined regions or the like. These filters may operate on a point(vertex) topology, a face topology, and/or a cell topology to filterdown to only the topological elements that meet the criteria. Theresulting subset of the model geometry is then provided for display.

FIG. 9 is a process flow diagram showing a method for providingvisualizations of data that represents a physical object according toexemplary embodiments of the present techniques. The process isgenerally referred to by the reference number 900. The process 900 maybe executed using one or more computer components of the type describedbelow with reference to FIG. 11. Such computer components may compriseone or more tangible, machine-readable media that storescomputer-executable instructions. The process 900 begins at block 902.

At block 904, an unstructured grid that corresponds to athree-dimensional physical structure is defined. The unstructured gridmay comprise data representative of a property of interest in thethree-dimensional physical structure.

At block 906, a probe comprising an object that comprises a set oftopological elements is defined. According to an exemplary embodiment ofthe present techniques, at least one of the topological elements doesnot share a common plane with the remainder of the set of topologicalelements. At block 908, a visual representation of the unstructured griddata is provided on the geometry defined by the probe. The process endsat block 910.

FIG. 10 is a process flow diagram showing a method for producinghydrocarbons from an oil and/or gas field using a visualization of datadescribing a physical structure according to exemplary embodiments ofthe present techniques. The process is generally referred to by thereference number 1000. Those of ordinary skill in the art willappreciate that the present techniques may facilitate the production ofhydrocarbons by producing visualizations that allow geologists,engineers and the like to determine a course of action to take toenhance hydrocarbon production from a subsurface region. By way ofexample, a visualization produced according to an exemplary embodimentof the present techniques may allow an engineer or geologist todetermine a well placement to increase production of hydrocarbons from asubsurface region. At block 1002, the process begins.

At block 1004, an unstructured grid that corresponds to athree-dimensional physical structure of the oil and/or gas field isdefined. The unstructured grid may comprise a plurality of cells thatembody data representative of a property of interest in the oil and/orgas field.

At block 1006, a probe comprising an object that comprises a set oftopological elements is defined. As described herein, at least one ofthe topological elements does not share a common plane with theremainder of the set of topological elements. At block 1008, a visualrepresentation of the unstructured grid data is produced on the geometrydefined by the probe. Hydrocarbons are extracted from the oil and/or gasfield based on the visualization, as shown at block 1010. At block 1012,the process ends.

FIG. 11 is a block diagram of a computer network that may be used toperform a method for providing visualizations of data that represents aphysical object according to exemplary embodiments of the presenttechniques. A central processing unit (CPU) 1101 is coupled to systembus 1102. The CPU 1101 may be any general-purpose CPU, although othertypes of architectures of CPU 1101 (or other components of exemplarysystem 1100) may be used as long as CPU 1101 (and other components ofsystem 1100) supports the inventive operations as described herein. TheCPU 1101 may execute the various logical instructions according tovarious exemplary embodiments. For example, the CPU 1101 may executemachine-level instructions for performing processing according to theoperational flow described above in conjunction with FIG. 9 or FIG. 10.

The computer system 1100 may also include computer components such as arandom access memory (RAM) 1103, which may be SRAM, DRAM, SDRAM, or thelike. The computer system 1100 may also include read-only memory (ROM)1104, which may be PROM, EPROM, EEPROM, or the like. RAM 1103 and ROM1104 hold user and system data and programs, as is known in the art. Thecomputer system 1100 may also include an input/output (I/O) adapter1105, a communications adapter 1111, a user interface adapter 1108, anda display adapter 1109. The I/O adapter 1105, the user interface adapter1108, and/or communications adapter 1111 may, in certain embodiments,enable a user to interact with computer system 1100 in order to inputinformation.

The I/O adapter 1105 preferably connects a storage device(s) 1106, suchas one or more of hard drive, compact disc (CD) drive, floppy diskdrive, tape drive, etc. to computer system 1100. The storage device(s)may be used when RAM 1103 is insufficient for the memory requirementsassociated with storing data for operations of embodiments of thepresent techniques. The data storage of the computer system 1100 may beused for storing information and/or other data used or generated asdisclosed herein. The communications adapter 1111 may couple thecomputer system 1100 to a network 1112, which may enable information tobe input to and/or output from system 1100 via the network 1112 (forexample, the Internet or other wide-area network, a local-area network,a public or private switched telephony network, a wireless network, anycombination of the foregoing). User interface adapter 1108 couples userinput devices, such as a keyboard 1113, a pointing device 1107, and amicrophone 1114 and/or output devices, such as a speaker(s) 1115 to thecomputer system 1100. The display adapter 1109 is driven by the CPU 1101to control the display on a display device 1110 to, for example, displayinformation or a representation pertaining to a portion of a subsurfaceregion under analysis, such as displaying data corresponding to aphysical property of interest, according to certain exemplaryembodiments.

The architecture of system 1100 may be varied as desired. For example,any suitable processor-based device may be used, including withoutlimitation personal computers, laptop computers, computer workstations,and multi-processor servers. Moreover, embodiments may be implemented onapplication specific integrated circuits (ASICs) or very large scaleintegrated (VLSI) circuits. In fact, persons of ordinary skill in theart may use any number of suitable structures capable of executinglogical operations according to the embodiments.

The present techniques may be susceptible to various modifications andalternative forms, and the exemplary embodiments discussed above havebeen shown only by way of example. However, the present techniques arenot intended to be limited to the particular embodiments disclosedherein. Indeed, the present techniques include all alternatives,modifications, and equivalents falling within the spirit and scope ofthe appended claims.

What is claimed is:
 1. A method for providing a visualization of datadescribing a physical structure, the method comprising: defining anunstructured grid that corresponds to a three-dimensional physicalstructure, the unstructured grid comprising data representative of aproperty of interest; defining a probe as an object that comprises a setof topological elements, at least one of which does not share a commonplane; and providing a visualization of the unstructured grid data onthe geometry defined by the probe.
 2. The method recited in claim 1,wherein the probe comprises a three-dimensional polyhedron.
 3. Themethod recited in claim 1, wherein the probe comprises a sphere.
 4. Themethod recited in claim 1, wherein the probe comprises a closedthree-dimensional surface.
 5. The method recited in claim 1, comprisingproducing a volume rendering within a closed space defined by the probe.6. The method recited in claim 1, comprising producing a volumerendering within a space defined by a distance and/or a direction fromthe probe.
 7. The method recited in claim 1, comprising: defining astructured grid within a space defined by the probe; and producing avolume rendering within the structured grid.
 8. The method recited inclaim 1, comprising: moving the probe to a different location; andproviding a visualization of the unstructured grid on the geometrydefined by the probe.
 9. The method recited in claim 1 wherein the probeis defined by a distance from a separate object.
 10. The method recitedin claim 9, wherein the distance is a directionless distance.
 11. Themethod recited in claim 9, wherein the distance is a vector distance.12. The method recited in claim 9, wherein the separate object is ageologic feature of interest.
 13. The method recited in claim 9, furthercomprising: defining an offset distance from a separate object; anddefining the probe using a vector distance from the offset.
 14. Themethod recited in claim 1 wherein the probe is defined based on anintersection of the unstructured grid and a separate object.
 15. Themethod recited in claim 1, wherein the probe is a first probe, andfurther comprising: defining a second probe as an object that comprisesa set of topological elements, at least one of which does not share acommon plane; and defining a combined probe as an object that is aproduct of a Boolean operation on the first probe and the second probe.16. The method recited in claim 1, wherein the probe is a first probe,and further comprising: defining a second probe as an object thatcomprises a set of topological elements, at least one of which does notshare a common plane; and linking the first probe and the second probesuch that movement of one of the probes is reflected by movement of theother of the probes.
 17. The method recited in claim 1, furthercomprising: modifying the definition of the probe such that the probehas a changed geometry; and providing a visualization of theunstructured grid on the probe with the changed geometry.
 18. The methodrecited in claim 17, wherein modifying the definition of the probecomprises changing a location of less than all vertices defining theprobe.
 19. The method recited in claim 17, wherein modifying thedefinition of the probe comprises adding or deleting vertices to theprobe.
 20. The method recited in claim 1, further comprising: accountingfor time-based changes to at least one of the probe, a geometry of theprobe, a geometry of the unstructured grid, and the data; and providinga visualization of the time-based changes.
 21. A computer system that isadapted to provide a visualization of data describing a physicalstructure, the computer system comprising: a processor; and a tangible,machine-readable storage medium that stores machine-readableinstructions for execution by the processor, the machine-readableinstructions comprising: code that, when executed by the processor, isadapted to cause the processor to define an unstructured grid thatcorresponds to a three-dimensional physical structure, the unstructuredgrid comprising data representative of a property of interest; codethat, when executed by the processor, is adapted to cause the processorto define a probe as an object that comprises a set of topologicalelements, at least one of which does not share a common plane; and codethat, when executed by the processor, is adapted to cause the processorto provide a visualization of the unstructured grid data on the geometrydefined by the probe.
 22. The computer system recited in claim 21,wherein the probe comprises a three-dimensional polyhedron.
 23. Thecomputer system recited in claim 21, wherein the probe comprises asphere.
 24. The computer system recited in claim 21, wherein the probecomprises a closed three-dimensional surface.
 25. The computer systemrecited in claim 21, comprising code that, when executed by theprocessor, is adapted to cause the processor to produce a volumerendering within a closed space defined by the probe.
 26. The computersystem recited in claim 21, comprising code that, when executed by theprocessor, is adapted to cause the processor to produce a volumerendering within a space defined by a distance and/or a direction fromthe probe.
 27. The computer system recited in claim 21, comprising: codethat, when executed by the processor, is adapted to cause the processorto define a structured grid within a space defined by the probe; andcode that, when executed by the processor, is adapted to cause theprocessor to produce a volume rendering within the structured grid. 28.The computer system recited in claim 21, comprising: code that, whenexecuted by the processor, is adapted to cause the processor to move theprobe to a different location; and code that, when executed by theprocessor, is adapted to cause the processor to provide a visualizationof the unstructured grid on the geometry defined by the probe.
 29. Amethod for producing hydrocarbons from an oil and/or gas field using avisualization of data describing a physical structure, the methodcomprising: defining an unstructured grid that corresponds to athree-dimensional physical structure of the oil and/or gas field, theunstructured grid comprising data representative of a property ofinterest in the oil and/or gas field; defining a probe as an object thatcomprises a set of topological elements, at least one of which does notshare a common plane; providing a visualization of the unstructured griddata on the geometry defined by the probe; and extracting hydrocarbonsfrom the oil and/or gas field based on the visualization.
 30. The methodrecited in claim 29, wherein the probe comprises a sphere.
 31. Themethod recited in claim 29, wherein the probe comprises a closedthree-dimensional surface.
 32. The method recited in claim 29,comprising producing a volume rendering within a closed space defined bythe probe.